Fact-checking AI-written contractor content means verifying every statement that could influence safety, money, service decisions or trust. A fluent draft can contain outdated rules, invented statistics, false product claims and confident technical errors. Editors need a claim-by-claim process, not a final request for the AI to “double-check itself.”
- Quick answer
- Separate facts from advice and marketing
- Rank claims by consequence
- Use a source hierarchy
- Verify that the source supports the exact claim
- Check dates and changing information
- Verify local applicability
- Use qualified expert review
- Check company-specific claims
- Check images and captions
- Audit citations and links
- Use a claim ledger
- Do not fabricate citations
- Check calculations separately
- Run a contradiction review
- Editorial approval workflow
- Verify AI summaries of sources
- Check safety instructions as a complete sequence
- Validate SEO elements
- Use a two-person rule for high-risk content
- Create correction procedures
- Fact-checking checklist
- A fact-checking example
- Verify quotations and testimonials
- Check generated FAQs
- Review competitor comparisons
- Validate accessibility claims and structure
- Keep an update queue
- Use publication stop criteria
- Frequently asked questions
- Can AI fact-check its own article?
- How many sources should an article use?
- Are citations necessary for every sentence?
- Can competitor blogs be sources?
- What if expert opinions differ?
- How often should articles be reviewed?
- Related Oivic guides
- Authoritative resources
- Publish only what the company can support
Quick answer
Extract factual claims from the draft, rank them by risk, and verify them against current primary sources and qualified company experts. Remove or qualify unsupported statements, confirm local scope and dates, test every link, preserve a source log, and assign an owner and review date before publishing.
Separate facts from advice and marketing
Highlight numbers, dates, definitions, laws, code claims, safety instructions, product specifications, prices, warranty statements, local conditions and company proof. Also flag comparisons such as “best,” “fastest” or “lasts longer.”
Opinions need clear framing; factual implications still need evidence.
Rank claims by consequence
- Critical: safety, electrical, gas, structural, health, legal and financial instructions.
- High: price, warranty, permit, licensing, product performance and customer commitments.
- Medium: statistics, market claims, timelines and comparisons.
- Low: general descriptive context with little decision impact.
Critical claims require qualified review and current authoritative sources.
Use a source hierarchy
| Claim | Preferred source |
|---|---|
| Local rule or permit | Relevant government authority |
| Safety practice | Regulator, standards body or qualified professional |
| Product specification | Current manufacturer technical document |
| Company service or price | Approved internal source with date |
| Statistic | Original study, agency or dataset |
| Software capability | Current official product documentation |
Blogs can help find a source but should not replace the original when it is available.
Verify that the source supports the exact claim
A source about average national cost does not prove a local fixed price. A manufacturer’s laboratory result may not support a universal real-world lifespan. Read conditions, geography, date and methodology.
Check dates and changing information
Mark software features, prices, laws, incentives, product availability and office information for frequent review. Add “accessed” or review dates to the editorial log. Remove a date only when the claim is genuinely stable, not to hide staleness.
Verify local applicability
Codes, permits, licensing, rebates, weather and utilities vary. Name the jurisdiction and link to its source. When local rules differ, explain that readers should confirm with the applicable authority.
Use qualified expert review
A technician or manager should review technical meaning, service fit and customer expectations. Legal, employment, tax and safety questions require appropriately qualified review. AI is not the approver.
Check company-specific claims
Verify years in business, licenses, service area, response time, warranties, team size, reviews, project totals and awards. Do not round numbers upward or use generated customer quotes. Keep supporting records.
Check images and captions
Confirm that real project images are the company’s and permitted for use. Label stock, rendering and AI illustration accurately. Do not let a caption imply a generated image is a local completed job.
Audit citations and links
Open every source. Confirm it is authoritative, current, secure and directly supports the nearby claim. Avoid search-result links and link farms. Review internal URLs for accidental nested paths.
Use a claim ledger
| Claim | Risk | Source | Reviewer | Review date |
|---|---|---|---|---|
| Example safety instruction | Critical | Approved authority | Qualified reviewer | Short interval |
| Software feature | Medium | Official documentation | Editor | After product update |
| Company warranty | High | Current approved terms | Manager | After policy change |
Do not fabricate citations
AI may generate plausible titles, organizations or URLs. Search for the original, open it and verify the document. If the source cannot be found, remove the citation and unsupported claim.
Check calculations separately
Recalculate examples in a spreadsheet or controlled tool. Verify units, percentages, totals and assumptions. Language models can make arithmetic mistakes while explaining them confidently.
Run a contradiction review
Compare the introduction, tables, FAQ and CTA. Long AI drafts may state one time range early and another later. Check related articles and service pages for conflicting company information.
Editorial approval workflow
- Writer labels claims and sources.
- Editor verifies low- and medium-risk facts.
- Qualified expert reviews technical and high-risk claims.
- SEO editor checks intent, links and metadata without changing facts.
- Publisher records version, reviewers and review date.
Verify AI summaries of sources
Do not rely on a generated summary of a document without opening the source. Check whether the AI omitted limitations, confused a proposal with a final rule or attributed a statement to the wrong organization. For PDFs, verify the relevant section and publication date.
When a source is ambiguous, quote sparingly and preserve context rather than making the claim broader.
Check safety instructions as a complete sequence
A sentence can be technically true but unsafe when an earlier warning or later condition is missing. Have a qualified reviewer examine the full action sequence, intended audience and stop conditions. Avoid DIY instructions for work that requires licensed or trained professionals.
Validate SEO elements
Check that the title, description and FAQ do not overstate the article. A cautious body cannot support a headline promising a guaranteed result. Ensure image alt text, schema and CTA use the same verified facts.
Use a two-person rule for high-risk content
One qualified reviewer checks technical or legal meaning; another editor checks whether the published wording, links and visuals preserved that approval. Record both. This catches late edits that accidentally reintroduce a removed claim.
Create correction procedures
Provide an internal and public way to report an error. When a material issue is confirmed, correct the article, related pages and snippets; document the date and assess whether customers need direct clarification. Do not silently leave conflicting copies.
Fact-checking checklist
- Every number, date and comparison is identified.
- High-consequence claims have qualified review.
- Primary sources were opened and read.
- Source scope matches geography and conditions.
- Calculations were independently reproduced.
- Company claims match current records.
- Images and captions do not imply false evidence.
- Links work and support nearby text.
- FAQ, metadata and schema match the article.
- Review owner and update date are recorded.
A fact-checking example
An AI draft says a coating “lasts 20 years in any garage.” The editor finds a manufacturer document describing performance under specified preparation and service conditions, not a universal lifespan. The claim is replaced with the verified system features, conditions and company warranty process. The article becomes more accurate and useful without pretending certainty.
Verify quotations and testimonials
Confirm the speaker, exact words, permission and context. Do not create a composite customer quote or clean up wording so extensively that it changes meaning. Reviews embedded in content should link to or preserve the authentic source according to platform rules.
Check generated FAQs
AI often creates confident FAQ answers that introduce claims absent from the main article. Treat each answer as new content. Verify price, timeline, warranty and legal language; remove questions the company cannot answer responsibly.
Review competitor comparisons
Comparative claims need current, fair evidence and matching scope. Avoid saying a product or method is always inferior. Explain conditions, tradeoffs and the basis for comparison. Marketing and legal review may be appropriate.
Validate accessibility claims and structure
Use meaningful headings, descriptive links, table headers, accurate alt text and readable language. Do not claim compliance from an automated score alone. Test important interactions and seek qualified accessibility review where appropriate.
Keep an update queue
Automate alerts for source changes, broken links and review dates, but assign human owners. Prioritize articles with safety, price, product, software or local-rule claims. Record what changed and whether related content needs correction.
Use publication stop criteria
Do not publish when a high-risk claim lacks evidence, expert review is incomplete, a cited source cannot be opened, local applicability is uncertain or images create a misleading impression. Missing a publishing date is less costly than distributing unsafe information.
Give editors authority to use that stop without pressure to meet a content quota. Escalate disagreements to the accountable subject owner, not back to the writing model.
After approval, lock or track material factual sections so routine SEO edits do not silently change reviewed meaning. Reopen expert review when a substantive claim, instruction or comparison changes.
Keep the prior approved version and its supporting evidence available.
Document every substantive correction clearly.
Frequently asked questions
Can AI fact-check its own article?
It can suggest claims to verify, but independent sources and human review are required.
How many sources should an article use?
Enough to support material claims. Quality and direct relevance matter more than count.
Are citations necessary for every sentence?
No, but specific, changing, technical and high-consequence claims need support.
Can competitor blogs be sources?
Use them to discover questions, not as the preferred evidence when primary sources exist.
What if expert opinions differ?
Represent uncertainty and scope. Do not force one universal answer.
How often should articles be reviewed?
Based on claim risk and change rate. High-risk and changing topics need shorter intervals.
Related Oivic guides
Authoritative resources
- Google Search guidance on helpful, reliable content
- NIST Generative AI Profile
- FTC information on deceptive AI claims
Publish only what the company can support
Oivic helps contractors turn AI drafts into evidence-led content with accountable review and maintenance.
